Select Publications
Preprints
2024, Explaining EDA synthesis errors with LLMs, , http://arxiv.org/abs/2404.07235v1
,2023, LLMs Cannot Reliably Identify and Reason About Security Vulnerabilities (Yet?): A Comprehensive Evaluation, Framework, and Benchmarks, , http://arxiv.org/abs/2312.12575v2
,2023, AutoChip: Automating HDL Generation Using LLM Feedback, , http://dx.doi.org/10.48550/arxiv.2311.04887
,2023, Towards the Imagenets of ML4EDA, , http://dx.doi.org/10.48550/arxiv.2310.10560
,2023, Are Emily and Greg Still More Employable than Lakisha and Jamal? Investigating Algorithmic Hiring Bias in the Era of ChatGPT, , http://arxiv.org/abs/2310.05135v1
,2023, Dcc --help: Generating Context-Aware Compiler Error Explanations with Large Language Models, , http://arxiv.org/abs/2308.11873v2
,2023, VeriGen: A Large Language Model for Verilog Code Generation, , http://arxiv.org/abs/2308.00708v1
,2023, LLM-assisted Generation of Hardware Assertions, , http://arxiv.org/abs/2306.14027v1
,2023, FLAG: Finding Line Anomalies (in code) with Generative AI, , http://arxiv.org/abs/2306.12643v1
,2023, Chip-Chat: Challenges and Opportunities in Conversational Hardware Design, , http://dx.doi.org/10.1109/MLCAD58807.2023.10299874
,2023, REMaQE: Reverse Engineering Math Equations from Executables, , http://dx.doi.org/10.48550/arxiv.2305.06902
,2023, Fixing Hardware Security Bugs with Large Language Models, , http://arxiv.org/abs/2302.01215v1
,2023, A survey of Digital Manufacturing Hardware and Software Trojans, , http://arxiv.org/abs/2301.10336v1
,2022, Benchmarking Large Language Models for Automated Verilog RTL Code Generation, , http://arxiv.org/abs/2212.11140v1
,2022, Don't CWEAT It: Toward CWE Analysis Techniques in Early Stages of Hardware Design, , http://dx.doi.org/10.1145/3508352.3549369
,2022, Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants, , http://arxiv.org/abs/2208.09727v4
,2022, High-Level Approaches to Hardware Security: A Tutorial, , http://dx.doi.org/10.1145/3577200
,2022, Pop Quiz! Can a Large Language Model Help With Reverse Engineering?, , http://arxiv.org/abs/2202.01142v1
,2021, Examining Zero-Shot Vulnerability Repair with Large Language Models, , http://arxiv.org/abs/2112.02125v3
,2021, Needle in a Haystack: Detecting Subtle Malicious Edits to Additive Manufacturing G-code Files, , http://dx.doi.org/10.1109/LES.2021.3129108
,2021, Runtime Interchange for Adaptive Re-use of Intelligent Cyber-Physical System Controllers, , http://arxiv.org/abs/2110.01974v1
,2021, Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions, , http://arxiv.org/abs/2108.09293v3
,2021, FLAW3D: A Trojan-based Cyber Attack on the Physical Outcomes of Additive Manufacturing, , http://arxiv.org/abs/2104.09562v1
,2020, DAVE: Deriving Automatically Verilog from English, , http://dx.doi.org/10.1145/3380446.3430634
,2020, Designing Neural Networks for Real-Time Systems, , http://dx.doi.org/10.1109/LES.2020.3009910
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